Models for: Reflectance spectroscopy allows rapid, accurate, and non-destructive estimates of functional traits from pressed leaves
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June 20, 2022
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Models for: Reflectance spectroscopy allows rapid, accurate, and non-destructive estimates of functional traits from pressed leaves
Published Date
2022-06-23
Author Contact
Cavender-Bares, Jeannine
cavender@umn.edu
cavender@umn.edu
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Statistical Computing Software Code
Abstract
More than ever, ecologists seek to employ herbarium collections to estimate plant functional traits from the past and across biomes. However, many trait measurements are destructive, which may preclude their use on valuable specimens. Researchers increasingly use reflectance spectroscopy to estimate traits from fresh or ground leaves, and to delimit or identify taxa. Here, we extend this body of work to non-destructive measurements on pressed, intact leaves, like those in herbarium collections. Using 618 samples from 68 species, we used partial least-squares regression to build models linking pressed-leaf reflectance spectra to a broad suite of traits, including leaf mass per area (LMA), leaf dry matter content (LDMC), equivalent water thickness, carbon fractions, pigments, and twelve elements. We compared these models to those trained on fresh- or ground-leaf spectra of the same samples. Here, we present the model coefficients and a README that provides examples of how to apply them to other data.
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This submission contains the partial least-squares regression (PLSR) model coefficients to accompany the paper “Reflectance spectroscopy allows rapid, accurate, and non-destructive estimates of functional traits from pressed leaves” by Kothari et al. (2022) Methods in Ecology & Evolution. Each set of models for a given trait comprises a .csv file containing 100 models (rows) × wavelengths. The 100 models are derived from a jackknife analysis as described in the paper. To generate trait estimates using a model set, you apply them to the data (see below) and can take the mean or the full distribution of estimates.
Referenced by
Reflectance spectroscopy allows rapid, accurate, and non-destructive estimates of functional traits from pressed leaves Shan Kothari, Rosalie Beauchamp-Rioux, Etienne Laliberté, Jeannine Cavender-Bares bioRxiv 2021
https://doi.org/10.1101/2021.04.21.440856
Reflectance spectroscopy allows rapid, accurate, and non-destructive estimates of functional traits from pressed leaves” Kothari et al. (2022) Methods in Ecology & Evolution
https://doi.org/10.1101/2021.04.21.440856
Reflectance spectroscopy allows rapid, accurate, and non-destructive estimates of functional traits from pressed leaves” Kothari et al. (2022) Methods in Ecology & Evolution
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ASCEND NSF DBI: 2021898
CABO NSERC: 509190-2017
CABO NSERC: 509190-2017
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Suggested citation
Kothari, Shan; Beauchamp-Rioux, Rosalie; Laliberté, Etienne; Cavender-Bares, Jeannine. (2022). Models for: Reflectance spectroscopy allows rapid, accurate, and non-destructive estimates of functional traits from pressed leaves. Retrieved from the Data Repository for the University of Minnesota (DRUM), https://doi.org/10.13020/ycga-7e47.
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FreshAreaModels.zip
Fresh Area Models zip file
(31.82 MB)
FreshModels.zip
Fresh Models zip file
(35.35 MB)
GroundModels.zip
Ground Models zip file
(35.45 MB)
Pressed1300Models.zip
Pressed 1300 Models
(19.49 MB)
PressedAreaModels.zip
Pressed Area Models
(32.15 MB)
PressedModels.zip
Pressed Models
(35.49 MB)
README.html
README file html
(729.46 KB)
README.Rmd
README file R Markdown
(7.96 KB)
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